http://www.nitrc.org/forum/forum.php?forum_id=3380 <table border="0" width="100%"><tr><td align="left"/><td align="right"><a href="http://www.ncbi.nlm.nih.gov/sites/entrez?db=PubMed&amp;cmd=Link&amp;LinkName=PubMed_PubMed&amp;from_uid=22833038">Related Articles</a></td></tr></table> <p><b>Recent developments in multivariate pattern analysis for functional MRI.</b></p> <p>Neurosci Bull. 2012 Aug;28(4):399-408</p> <p>Authors: Yang Z, Fang F, Weng X</p> <p>Abstract<br/> Multivariate pattern analysis (MVPA) is a recently-developed approach for functional magnetic resonance imaging (fMRI) data analyses. Compared with the traditional univariate methods, MVPA is more sensitive to subtle changes in multivariate patterns in fMRI data. In this review, we introduce several significant advances in MVPA applications and summarize various combinations of algorithms and parameters in different problem settings. The limitations of MVPA and some critical questions that need to be addressed in future research are also discussed.<br/> </p><p>PMID: 22833038 [PubMed - in process]</p> en-us Copyright 2000-2026 NITRC OSI Fri, 01 May 2026 2:02:55 GMT http://blogs.law.harvard.edu/tech/rss NITRC RSS generator